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Record W2207805758 · doi:10.4271/2003-01-2101

Experimental and Numerical Studies of the Effects of Upper Surface Roughness on Aileron Performance

2003· article· en· W2207805758 on OpenAlexaff
P. J. Penna, Jinyou Su, G. F. Syms

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2003
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAileronSurface roughnessSurface finishMaterials scienceStructural engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Wind tunnel studies were carried out to observe the effects of distributed roughness on the upper surface of a NACA 4415 wing-aileron combination. Viscous analysis of the corresponding 2-D airfoil with an aileron was carried out using the 2-D structured multi-block Navier-Stokes (NS) solver NPARC. The two equation k-ω model was used without wall functions as it allows the specification of a surface roughness through the wall boundary condition. Three different configurations, i.e., the Fokker F-28 MK1000 aircraft with aileron deflections, a NASA LS(1)-0417 wing-flap combination and the NACA 4415 wing-aileron combination, were investigated using the 3-D potential/viscous interaction solver PMAL3D. The results of the experiment, 2-D and 3-D numerical calculations were analyzed and compared where suitable. Generally, the numerical studies were consistent with the experiments and showed similar reductions in maximum lift and stall angle of attack. It is also shown from the present work that roughness on an aircraft's lifting surfaces will have significant effects on its aerodynamics and controllability.</div>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.240
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2003
Admission routes1
Has abstractyes

Explore more

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